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_a10.1007/978-3-540-44767-2 _2doi |
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_a530.1 _223 |
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_aData Analysis in Cosmology _h[electronic resource] / _cedited by Vicent J. Martinez, Enn Saar, Enrique Martinez Gonzales, Maria Jesus Pons-Borderia. |
264 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2009. |
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300 |
_aXII, 636 p. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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_acomputer _bc _2rdamedia |
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_aonline resource _bcr _2rdacarrier |
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_atext file _bPDF _2rda |
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490 | 1 |
_aLecture Notes in Physics, _x0075-8450 ; _v665 |
|
505 | 0 | _aUniversal Tools -- The Sea of Wavelets -- Fisher Matrices and All That: Experimental Design and Data Compression -- Data Compression, Classification and Parameter Estimation. Methods: Examples from Astronomy -- Statistics of Cosmic Background Radiation -- Cosmic Microwave Background Anisotropies: The Power Spectrum and Beyond -- Cosmic Microwave Background Polarization Analysis -- Diffuse Source Separation in CMB Observations -- Techniques for Compact Source Extraction in CMB Maps -- Determination of Cosmological Parameters from Cosmic Microwave Background Anisotropies -- Cosmic Microwave Background Data Analysis: From Time-Ordered Data to Angular Power Spectra -- Statistics of Large-Scale Structure -- The Large-Scale Structure in the Universe: From Power Laws to Acoustic Peaks -- The Cosmic Web: Geometric Analysis -- Power Spectrum Estimation. I. Basics -- Power Spectrum Estiamtion II. Linear Maximum Likelihood -- to Higher Order Spatial Statistics in Cosmology -- Phase Correlations and Topological Measures of Large-Scale Structure -- Multiscale Methods -- Gaussian Fields and Constrained Simulations of the Large-Scale Structure -- Weak Gravitational Lensing -- Mass Reconstruction from Lensing. | |
520 | _aThe amount of cosmological data has dramatically increased in the past decades due to an unprecedented development of telescopes, detectors and satellites. Efficiently handling and analysing new data of the order of terabytes per day requires not only computer power to be processed but also the development of sophisticated algorithms and pipelines. Aiming at students and researchers the lecture notes in this volume explain in pedagogical manner the best techniques used to extract information from cosmological data, as well as reliable methods that should help us improve our view of the universe. | ||
650 | 0 | _aStatistics. | |
650 | 1 | 4 |
_aClassical and Quantum Gravitation, Relativity Theory. _0http://scigraph.springernature.com/things/product-market-codes/P19070 |
650 | 2 | 4 |
_aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. _0http://scigraph.springernature.com/things/product-market-codes/S17020 |
650 | 2 | 4 |
_aNumerical and Computational Physics, Simulation. _0http://scigraph.springernature.com/things/product-market-codes/P19021 |
700 | 1 |
_aMartinez, Vicent J. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
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700 | 1 |
_aSaar, Enn. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
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700 | 1 |
_aGonzales, Enrique Martinez. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
700 | 1 |
_aPons-Borderia, Maria Jesus. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
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710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
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_iPrinted edition: _z9783540860624 |
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_iPrinted edition: _z9783642063053 |
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_iPrinted edition: _z9783540239727 |
830 | 0 |
_aLecture Notes in Physics, _x0075-8450 ; _v665 |
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856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-540-44767-2 |
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